Introduction/Business Problem

A restaurant consolidator is looking to revamp its B-to-C portal using intelligent automation tech. It is in search of different matrix to identify and recommend restaurants. To make sure an effective model can be achieved it is important to understand the behaviour of the data in hand.

Preliminary data inspection

from above output we can infer that mostly values are which are null is in one coloumn i.e. Cuisines while as Resturant Name has 1 value which is missing which can be ignored. Hence we have to deal with null values of cuisines and make sure it does not affect our sample data

It can be infer from above that there are no duplicates in the dataset

Performing EDA

Maximum no. of restaurants is in New delhi i.e. 5473 and And there are about 46 restaurnts which are only 1 in a particular city

Hence 0.16 is the ratio between resturants that has table booking and those who do not have table booking

Percentage of restuarnts those are providing online delivery is 20.9%